The present invention is related to computer vision and image processing, and in particular to video-quality enhancement of images containing obscuring phenomena such as either snow and/or rain.
Computer vision and image processing relates broadly to any application that makes use of image data. Video-quality enhancement refers to image processing techniques that seek to improve or otherwise enhance the quality of the video data. Video-quality enhancement may be employed to enhance data prior to subsequent video analytic software used to analyze the video data, or may be used to improve the quality of an image (i.e., frame) or sequence of frames displayed to a user.
For example, video surveillance is one application in which video quality is often-times an issue. Whether video surveillance data is monitored by a human operator or by way of video analytic software that automatically detects the presence of threats or security breaches, the quality of the video data provided to the human operator or the video analytic system is important for improving the effectiveness of the system. In particular, surveillance systems are often-times required to operate in a variety of environments, including outdoor environments. The quality of the video data provided by the video systems is therefore susceptible to weather events such as rain and/or snow that will obscure or otherwise degrade the quality of the video data provided by the system. It would therefore be desirable to develop an automatic video-quality enhancement system and method for improving the quality of video data affected by the presence of snow and/or rain.